Educational qualifications mismatch in Europe. Is it demand or supply driven?

Ghignoni, Emanuela; Verashchagina, Alina

doi:10.1016/j.jce.2013.06.006

Cited by 57 publications

(42 citation statements)

References 45 publications

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“…The results very clearly support the view that overeducation is predominantly driven by an excess in the supply of educated labour with the ratio between the number of graduates in employment and the share of workers in professional occupations highly significant in both equations. This is consistent with job competition and assignment approaches and with previous empirical findings (Verhaest and van der Velden, 2013;Ghignoni et al, 2014). However, the marginal effects are small with the models suggesting that a 10 % increase in this ratio will drive male and female overeducation rates up by 0.5 and 0.7 parentage points respectively.…”

Section: Resultssupporting

confidence: 90%

“…Croce and Ghignoni (2012), in their pooled model for 26 European countries, found that the ratio of wages of graduates to those of less-qualified workers is associated with graduate overeducation and also that recession leads to overeducation, with graduates accepting jobs requiring less education than they possess. Ghignoni and Verashchagina (2014) explore determinants of individual overeducation risk in 10 European countries taking into account both supply -side and demand -side factors. This paper provides further evidence on the issue, with an assessment of the determinants of international variations in overeducation rates using European data and, in addition to structural factors, assesses the potential contribution of labour market uncertainty, labour market institutions, education funding mechanisms and migration as determining factors.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This approach to the measurement of overeducation is adopted due to the absence of alternative subjective based measures within EU-SILC, and it is similar to that adopted in previous studies (e.g. Croce et al, 2012;Ghignoni et al, 2014). Moreover, while it has been noted that this realized matches approach tends to show lower rates of overeducation than alternative measures based either on self-assessment of the job-skills match or detailed analysis of job 5 The number of available observations per region and country are displayed in table A1 in the Data Appendix.…”

Section: Datamentioning

confidence: 99%

“…For instance, Ghignoni and Verashchagina (2014) deployed several demand factors measured at NUTS2 level (incidence of patents application, gross fixed capital formation, expenditure per worker in R&D, proportion of professionals among employed and youth unemployment). Our approach is slightly different as we explicitly focus on factors that directly address supply and demand imbalances or mismatches, whereas, with the exception of the youth unemployment rates at NUTS 2 level, Ghignoni et al (2014) analyse demand and supply factors separately. Croce et al (2012) and Verhaest et al (2013) also found that measures related to excess supply of skilled labour were related to the incidence of overeducation.…”

Section: Labour Market Demand / Supply Indicators: Both the Job Compementioning

confidence: 99%

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Determinants of regional differences in rates of overeducation in Europe

Rodríguez

McGuinness

O’Connell

2017

Social Science Research

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This paper examines the factors determining variations in spatial rates of overeducation.A quantile regression model has been implemented on a sample of region-yearly data drawn from the EU Survey on Income and Living Conditions (EU-SILC) and several institutional and macroeconomic features captured from other data-sets. Potential determinants of overeducation rates include factors such as labour market risk, financial aid to university students, excess labour demand and institutional factors. We find significant effects both for labour market structural imbalances and institutional factors.The research supports the findings of micro based studies which have found that overeducation is consistent with an assignment interpretation of the labour market.Keywords: Overeducation, regional variation, mismatch JEL classification: C29; I21; J24 Highlights: Overeducation reacts to educated labour supply excess and university enrolment levels  There is limited evidence that overeducation is driven by high returns to education  Overeducation is explained by migration-and sectoral composition of employment  Structural factors play a significant role in determining overeducation rates

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Section: Resultssupporting

confidence: 90%

Section: Literature Reviewmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Labour Market Demand / Supply Indicators: Both the Job Compementioning

confidence: 99%

See 2 more Smart Citations

Determinants of regional differences in rates of overeducation in Europe

Rodríguez

McGuinness

O’Connell

2017

Social Science Research

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“…Individual characteristics may be more important than macro-level factors (Ghignoni and Verashchagina 2014). At the microeconomic level, five categories of factors have been found to affect the risk of overeducation: (1) ability, academic performance, and personality; (2) gender and age; (3) immigrant background; (4) labour market and job characteristics; and (5) characteristics of education.…”

Section: Determinants Of Job Polarization and Skills Mismatchmentioning

confidence: 99%

Imbalanced Job Polarization and Skills Mismatch in Europe

Sparreboom

Tarvid

2016

J Labour Market Res

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This paper considers the education of the labour force based on an analysis of trends in and the relationships between job polarization and skills mismatch. Both job polarization and skills mismatch have become topics of increasing interest, but relationships between the two have been relatively neglected in the literature. We argue that the relationship between polarization and skills mismatch is an empirical matter, which we analyse at both the macroeconomic and microeconomic level in European countries. A novel job polarization index (JPI) is proposed to measure imbalanced job polarization. It takes into account not only the change in the share of medium-level jobs, as is typical for measuring pure polarization, but also the imbalance between the change in high-level and low-level jobs. Skills mismatch at macrolevel is measured by a skills mismatch index (SMI), while traditional measures of undereducation and overeducation are used at the microeconomic level. At the macroeconomic level, we estimate a system of two equations, one for each of the country-level variables gauging polarization and mismatch, respectively. Imbalanced job polarization measured Electronic supplementary material The online version of this article (doi:10.1007/s12651-016-0196-y) contains supplementary material, which is available to authorized users.Responsibility for opinions expressed in this paper rests solely with the authors and does not constitute an endorsement by the ILO. by the JPI negatively affects skills mismatch at the macroeconomic level (SMI), but there is no significant reverse effect. Thereafter we consider the microeconomic level and study the determinants of mismatch using multi-level mixed effects logistic models. The effect of imbalanced job polarization on individual-level mismatch was arguably favourable for individuals in non-crisis time, decreasing overeducation risk although also increasing the chances of undereducation, both gauged using the normative measure, but unfavourable during the global financial crisis of 2008-2009 and the following two years.

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An analysis of educational mismatch on wages in the agroindustrial sector

Lasso‐Dela‐Vega,

Campos‐Soria,

García‐Pozo

2023

Agribusiness

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The food industry is one of the most important industries in developed economies. The progressive professionalization of its workforce and the persistent demand for low‐skilled employment in this sector may be leading to educational mismatch with its concomitant effects on wages and productivity. Yet the economic literature has not addressed wage structures, gender differences, and the composition of the labor force together in this food industry. We analyzed the effects of educational mismatch on wages in the Spanish food industry from a gender perspective. To this end, we used data from the 2018 Wage Structure Survey collected by the Spanish National Institute of Statistics. We applied the overeducated, required educated, undereducated specification to these data. The main results show that educational mismatch leads to gender wage differentials in this sector. The analysis also shows that the Spanish food industry places more value on men with adequate education and women with some level of overeducation. The results on occupational segregation show that the food industry penalizes access to female‐dominated occupations, and that this wage disadvantage is greater for female workers. We also observed wage differences in the remuneration of certain personal and professional factors that could be worsening the gender differentials in the Spanish food industry [EconLit Citations: I26, J16, J21, J24, J31].

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Educational qualifications mismatch in Europe. Is it demand or supply driven?

Cited by 57 publications

References 45 publications

Determinants of regional differences in rates of overeducation in Europe

Determinants of regional differences in rates of overeducation in Europe

Imbalanced Job Polarization and Skills Mismatch in Europe

An analysis of educational mismatch on wages in the agroindustrial sector

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